(Senior) Software Engineer Data Integration (all genders)
- Status
- Open
- Remote policy
- Not stated
- Employment type
- Not stated
- Salary
- 59,000-91,000 EUR / year
- Source
- germantechjobs
- First observed
- 2026-09-23 11:26 UTC
- Last seen
- 2026-09-23 11:26 UTC
- Source claims posted
- 2026-09-23 09:52 UTC
- Consecutive misses
- 2 of 3
What the posting says
Salary: 59.000 - 91.000 € per year
Requirements:
You have 2+ years of relevant experience in backend development with a focus on data engineering, API integration, or event-driven systems.
You have a degree in Computer Science, Data Science, Software Engineering, Electrical Engineering, Industrial Engineering, or a comparable field of study.
You have practical experience in Python programming and are familiar with common best practices.
You have experience with SQL databases, preferably PostgreSQL or TimescaleDB, in the area of data modelling and query design.
You have experience integrating with external APIs or streaming systems (e.g. Kafka, MQTT, REST or gRPC).
Ideally, you are familiar with IoT or energy domain protocols (e.g. MQTT, IEC104) and have worked with real-time data pipelines.
You are a team player and passionate about working with talented and inspiring people.
You are looking for technical challenges and pride yourself in finding smart and simple solutions for complex problems.
You are familiar with parts of our tech stack and are looking forward to keeping up with current industry best practices.
You are business-fluent in English (Level C1).
Responsibilities:
You build new measurement integrations end-to-end: connecting external IoT devices (via Kafka, MQTT, IEC104, REST, gRPC) through device registration and normalization to live data ingestion, transformation, and storage.
You design and improve the measurement integration framework to make adding new sources faster, more reliable, and more observable.
You own the full integration lifecycle — from raw external data to normalized, mapped measurements, including custom transformations and ID mappings.
You contribute to the existing ETL framework for importing and digitizing customer grid data from heterogeneous source formats.
You optimize existing components for performance, reliability, and transparency across batch and streaming workloads.
You have a continuous improvement mindset and actively look for ways to bring our code to industry best practices with confidence.
Technologies:
API
Backend
ETL
Hardware
IoT
Support
Kafka
MQTT
PostgreSQL
Python
REST
SQL
gRPC
Celery
Docker
FastAPI
Kanban
Kubernetes
Redis
pytest
More:
As (Senior) Software Engineer Data Integration (all genders), we design innovative software solutions that set our products apart from the masses. Within our Engineering team, we play an important role in further shaping and developing our platform. With a focus on real-time measurement data and system integration, we are the interface between external source systems — from IoT devices to grid operator APIs — and our Intelligent Grid Platform (IGP). In a dynamic team, we build and evolve the components that bring live measurement data and grid asset information reliably into the IGP. We work fully remote or from our office in Cologne in a hybrid model, with the option to work from abroad for up to three months per year from anywhere in the EU or the USA. We offer a modern tech stack, excellent hardware, 30 holidays plus 3 corporate holidays, health and mental wellbeing support, a monthly mobility budget, time for growth, regular tech and growth talks, a pension plan, and regular company and team events.
last updated 38 week of 2026
Quality
- + Salary range stated weight 35%
- x Remote policy stated weight 20%
- x Location stated weight 15%
- + Organisation stated weight 15%
- + Publication date stated weight 15%
Based on 3 observation(s).
- + Days open - fineOpen for 0 days so far
- + Reopen count - fineNever reopened
- + Salary range removed after publication - fineSalary range has not been removed since publication
- + Salary range narrowed - fineSalary range has not narrowed since publication
- + Missing/reappear cycles - fineNo missing-then-reappeared cycles observed
Timeline
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#943379 2026-09-23 11:26 UTCPublished
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#949712 2026-09-23 15:32 UTCNot seenMiss 1 in a row
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#951613 2026-09-23 17:41 UTCNot seenMiss 2 in a row